The wireless local area network (WLAN) standard, IEEE 802.11-2007, mandates supporting multiple modulation schemes with different forward error correction (FEC) schemes at the physical layer of a communication channel. Therefore, all devices implementing the IEEE 802.11-2007 standard support a fixed number of distinct modulation schemes. As a result, support a fixed number of different data rates. For example, the Orthogonal frequency-division multiplexing (OFDM) subsystem (IEEE 802.11a, g and n) provides a WLAN with data rates of 6, 9, 12, 18, 24, 36, 48 and 54 Mb/s. Of these, data rates 6, 12 and 24 Mb/s are mandatory.
However, the implementation of the above described standard results in unfair allocation of resources because client devices that can support higher data rates sometimes are forced to accept lower data rates. For example, the client devices that are far away from an access point usually fall back to communication at lower modulation schemes, as packets transmitted at lower modulation schemes can be demodulated without errors even if the packets are received at a lower signal strength. Packets sent at lower modulation schemes (e.g., lower data rates), take longer to reach the destination entity than packets transmitted using higher modulation schemes. According to the IEEE 802.11-2007 standard, by default, whenever a client device wants to transmit a data packet, the client device can transmit only one Media Access Control (MAC) layer packet when the client devices wins contention to the medium.
Therefore, all client devices of an access point generally receive equal opportunities to transmit data packets. The same is applicable to the downlink communication channel. This results in unfairness to client devices which can support higher data rates because the client devices that use lower modulation schemes occupy the channel for a long time when the lower-modulation client devices win contention to the medium. Therefore, the client devices that use higher modulation schemes do not receive data rates proportional to their channel conditions. As a result, far-away client devices bring down the performance of every node in the network. The following two examples further explain this problem.
In the first example, suppose there is a WLAN network with an access point “AP” and two clients C1 and C2. Both clients C1 and C2 are located close to the access point AP and support the highest modulation scheme resulting in data rates of 54 Mbps (highest in the 802.11g standard). If both of the clients C1 and C2 operate together, they both receive a data rate of approximately 54/2 Mbps. However, the throughput will probably be decreased because of overheads such as headers and acknowledgments (ACKs), and other physical layer complexities. Next, suppose that client C2 moves away from the access point AP and can support only the 6 Mbps data rate. Now, when clients C1 and C2 operate together, both get a data rate of approximately 6/2 Mbps even though client C1 has not changed its location. As a result, client C1's throughput decreased to approximately 4 Mbps because client C2's data packets take longer to reach the access point AP and both clients C1 and C2 share the medium on a packet-by-packet basis.
The second example relates to digital television (DVT) whitespace. For example, the Federal Communications Commission (FCC) has recently opened up unused TV spectrum in 50-698 MHz for unlicensed access of various kinds. This previously unused TV spectrum is referred to as DTV whitespace. Designing WLAN access technology over the DTV whitespace appears to be a promising use for the DTV whitespace spectrum. The WLAN networks that include such DTV whitespace spectrum will have much longer frequency ranges than the conventional WLAN network (2.4 GHz) because lower frequencies (e.g., 60-698 MHz) may propagate farther. Therefore, the problem of unfairness as shown in the first example will be exacerbated in a DTV whitespace WLAN network because the access points of this network will have longer ranges, and as a result, more client devices being further away from the access point. Therefore, this type of network has more chances of showing poor performance.
Conventional methods share the frequency spectrum by allocating frequency spectrum in a “max-min” fair manner (i.e., the data rate of the client which can achieve minimum data rate is maximized). However, this type of system decreases performance as a whole. A number of conventional approaches have been considered to improve performance, as described below.
The first conventional approach uses “client repeaters.” For example, in this approach, high data rate client devices operate as repeaters for low data rate client devices. This mechanism is activated whenever the client devices (i.e., nodes) detect that it is beneficial to use this “repeater” mechanism as opposed to operating in the low data rate mode collectively. It also has been suggested to use network coding to alleviate re-transmission overheads of the repeater operation. However, this conventional approach depends on the presence of co-operating clients and involves the clients switching between operating modes (e.g., client mode to ad hoc mode) frequently. The mode-switching overheads make the implementation of this approach difficult in current hardware. Also, this conventional approach involves maintaining a table of mapping between signal strength to an expected data rate. However, signal strength based mapping to data rates may be inaccurate because this mapping does not completely account for packet losses. Also, this approach does not guarantee proportional fairness theoretically.
The second conventional approach uses an “idle sense.” For example, in this approach, the contention windows of the contending hosts in a random access network are adjusted so that the contention widows converge to a value that is optimal for the network conditions. This approach addresses the rate unfairness issue when using time-fairness as the optimizing function. Although this mechanism ensures time-fairness, it does not ensure good channel utilization and may result in a waste of spectrum in the presence of only slow data rate clients because the optimal number of idle slots is calculated for a fixed bit rate.
The third conventional approach uses an opportunistic media access. For example, this approach allows clients that sense good channel conditions to transmit a burst of packets proportional to the data rate these clients are sensing. For example, this scheme allows a client sensing an 11 Mbps data rate to transmit five times more than a client sensing a 2 Mbps data rate. However, the main drawback of this approach is that the scheme relies on an RTS/CTS exchange between the stations to inform other stations in the network of ongoing communications. As a result, this approach is more suited to ad-hoc networks because in a typical infrastructure network, the RTS/CTS exchanges are usually turned off. Also, this approach may lead to unnecessary delays when several clients sensing very good channel conditions belong to the same network because the burst size is calculated with respect to the lowest data rate possible and not the lowest data rate among present clients.
The fourth conventional approach uses a time based fairness approach. This approach implements downlink queues at the access point and schedules packets for each client such that all clients get equal time-share. In the uplink channel, the protocol relies on being able to request clients to delay the transmission of a data packet till the access point schedules the transmission of the data packet. As a result, this approach requires setting up of as many queues at the access point as the number of clients. However, this implementation does not scale with the number of clients, and is dependant on measuring channel occupancy of each packet. Also, it is difficult to track this information at the access point for uplink traffic because of multi-rate retransmissions. Also, the implementation of this scheme for uplink is complicated because the access point must schedule every uplink packet in a centralized manner.